Jan M. Köhler

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 154 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it; #27,128 of 35,345 by trust here, #15,236 by citations
• Computer Vision and Pattern Recognition — 55 citations into it
• Safety, Robustness & Interpretability — 22 citations into it
• Model Architectures — 12 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it
• Biophysics — 8 citations into it
• Optimization & Training — 7 citations into it

Whom Jan M. Köhler trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Christian Szegedy
4. Diederik P. Kingma
5. Ilya Sutskever
6. Kaiming He
7. Yoshua Bengio
8. Yann LeCun
9. Karen Simonyan
10. Matthew D. Zeiler

Who trusts Jan M. Köhler overall

1. D. V. Carvalho

Papers from Jan M. Köhler's perspective

Ordered by how strongly the researchers Jan M. Köhler trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet Large Scale Visual Recognition Challenge
8. Attention is All you Need (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• The Power of Ensembles for Active Learning in Image Classification (2018) — 763 citations
• Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks (2019) — 132 citations
• Weakly-supervised localization of diabetic retinopathy lesions in retinal fundus images (2017) — 152 citations